AU2021100314A4 - System for issue alert of security breach using machine learning and fuzzy logic - Google Patents

Abstract

SYSTEM FOR ISSUE ALERT OF SECURITY BREACH USING MACHINE LEARNING AND FUZZY LOGIC ABSTRACT The present invention relates to System for issue alert of security breach using machine learning and fuzzy logic. The objective of the present invention is to solve the problems in the prior art related to adequacies in technologies of sect of transmission devices. The machine learning and fuzzy logic is used to for providing alert on the security breach. 29 DRAWINGS Applicants: Pramoda Patro & Other MACHINE LEARNING PROCESSOR Deep Learning UNIT SENSOLR UI MODULE ii FUZZY LOGIC ALERT SYSTEN ((a)) FIGURE 1 Date 1 8 th day of January, 2021 30

Description

DRAWINGS

Applicants: Pramoda Patro & Other

MACHINE LEARNING PROCESSOR Deep Learning UNIT SENSOLR UI MODULE ii FUZZY LOGIC

ALERT SYSTEN

((a))

FIGURE 1

Date 1 8 th day of January, 2021

SYSTEM FOR ISSUE ALERT OF SECURITY BREACH USING MACHINE LEARNING AND FUZZY LOGIC FIELD OF INVENTION

[001]. The present invention relates to the technical field of machine

learning and fuzzy logic.

[002]. More particularly, the present invention is related to System for issue

alert of security breach using machine learning and fuzzy logic

BACKGROUND & PRIOR ART

[003]. The subject matter discussed in the background section should not

be assumed to be prior art merely as a result of its mention in the background

section. Similarly, a problem mentioned in the background section or

associated with the subject matter of the background section should not be

assumed to have been previously recognized in the prior art. The subject

matter in the background section merely represents different approaches,

which in-and-of-themselves may also be inventions.

[004]. A common problem faced by the manufacturing industry is the costs

associated with delays in production as a consequence of mechanical

problems such as equipment failure or physical degradation due to lack of

attention and maintenance in a timely manner. It is of great interest for these

businesses to be able to predict in advance the occurrence of such

phenomena to proactively correct them before they occur and thus avoid

costs associated with the downtime incurred by a technical stoppage.'

[005]. The present invention relates generally to the field of safety

alerts, and more particularly to machine learning.

[006]. Safety alerts includes identifying safety issues in, on and around

a location, where there is a risk to either members of the public or a private

organization. Typical approaches to determine unsafe conditions only

utilize a limited set of metrics and are rarely changed or updated. Machine

learning is a field of artificial intelligence directing towards generating a

predictive model. Based on a learning or feedback process, machine

learning updates and alters the model to provide more accurate predictions.

Fuzzy logic is an approach that instead of a typical yes or no, or binary,

decision being provided, a degree of truth or range between the typical

binary answer is derived.".

[007]. US20160239723A1 - ENHANCED HOME SECURITY SYSTEM

presents" solution is provided to enhance home security monitoring by pre

processing and post-processing home security surveillance data and by

using a trained security model. A security controller receives motion data

from motion sensors and digital cameras strategically installed in a home

and pre-processes the motion data to detect possible candidates for the

detected motion. The security controller is connected with a variety security

sensors installed for monitoring home environment. Each of the security

sensors sends an event signal to the security controller in response to a state

change of the security sensor. The security controller analyzes the state

changes and generates security alerts responsive to detection of security

violation. A security server connected to the security controller post

analyzes the security surveillance video data to identify humans and animals

responsible for the detected motion and trains a security model to guide the

real time security monitoring by the security controller."

[008]. US9053335B2 - Methods and systems for active data security

enforcement during protected mode use of a system presents "Systems and

method are provided for enforcing data security. One example method

includes receiving user identification information from a screen of a device

that is connectable to a database of secure information. The method includes

authenticating the user identification information. The authenticating

includes capturing image data of a user associated with the user

identification information. The method provides access to the database of

secure information upon authenticating the user identification information,

such that while the access is provided the capturing of the image data of the

user is maintained. The method includes recording data of user interactive

input and viewed images displayed on the screen while the access provided.

The method disables the access to the database of secure information upon

detecting a predefined security enforcement violation associated with an

activity by the user during access to the database. The method being

executed by a processor."

[009]. W02011061767AI - SMART SECURITY-SUPERVISION

SYSTEM presents "a security- supervision system (200) configured to

supervise security of a site (400) to be protected. The security-supervision

system (200) comprises a simulation software module (5) configured to

simulate in a virtual environment potential violations of the security of the

site (400) perpetrated by simulated attackers (424).

[0010]. US7532895B2 - Systems and methods for adaptive location tracking

presents "system for tracking location of a wireless device, the system

comprising: a system data store capable of storing one or more tracking

criteria and indicators of one or more wireless devices to track; a set of one

or more wireless receivers on one or more wireless sensors; the wireless

sensors monitoring wireless header information from a wireless packet

frame; a system processor in communication with the system data store and

the one or more wireless sensors, wherein the system processor comprises

one or more processing elements programmed or adapted to perform the

steps comprising of: (a) identifying a wireless device for tracking based

upon a combination of dynamic operational and security assessments

derived using data from the system data store, wherein the dynamic

operational and security assessments identify the wireless device for

tracking responsive to behavior of the wireless device, wherein the dynamic

operational and security assessments comprise wireless signature-based

tests, wireless protocol-based tests, wireless anomaly-based tests, and

wireless policy deviation-based tests, wherein the policy deviation-based

tests comprise a deviation from a set of three or more wireless policy

settings comprising wireless channel settings, wireless authentication

settings, wireless encryption settings,"

[0011]. US20020128769AI - Electronic vehicle monitoring system presents

"electronic Vehicle Monitoring System and Related method for tracking the

location of the location of motor vehicles, is disclosed which tracks the

location of plurality of motor vehicles at a particular location, to ascertain

the exact position at which any motor vehicle is parked. The system of the

present invention also automatically determines, when each motor vehicle

at a location enters or leaves the location or a particular area. The system of

the present invention also automatically determines which of plurality of

motor vehicles having a security violation. In addition, the system

immobilizes the vehicle if tamper to the vehicle mount Transceiver CPU or

GPS system is detected, and report said violation to a monitoring station.

The system also utilizes an Electronic Key Track"

[0012]. US20200053324A1- SECURITY AUTOMATION INA MOBILE

ROBOT presents "a commercial or industrial setting, such as an office

building or retail store. The robot can patrol one or more routes within a

building, and can detect violations of security policies by objects, building

infrastructure and security systems, or individuals. In response to the

detected violations, the robot can perform one or more security operations.

The robot can include a removable fabric panel, enabling sensors within the

robot body to capture signals that propagate through the fabric. In addition,

the robot can scan RFID tags of objects within an area, for instance coupled

to store inventory. Likewise, the robot can generate or update one or more

semantic maps for use by the robot in navigating an area and for measuring

compliance with security policies."

[0013]. US20190294800A1 - Security Policy Enforcement Based On

Dynamic Security Context Updates presents "An information handling

system (IHS) includes a memory having a BIOS, at least one sensor that

generates security related data for the IHS, a controller, and one or more O

drivers. The memory, at least one sensor and controller operate within a

secure environment of the IHS; the IO driver(s) operate outside of the

secure environment. The controller includes a security policy management

engine, which is executable during runtime of the IHS to continuously

monitor security related data generated by the at least one sensor, determine

whether the security related data violates at least one security policy rule

specified for the IHS, and provide a notification of security policy violation

to the BIOS, if the security related data violates at least one security policy

rule. The IO driver(s) include a security enforcement engine, which is

executable to receive the notification of security policy violation from the

BIOS, and perform at least one security measure in response thereto."

[0014]. US8909926B2 - System and methodology providing automation

security analysis, validation, and learning in an industrial controller

environment presents "a system and methodology facilitating automation

security in a networked-based industrial controller environment. Various

components, systems and methodologies are provided to facilitate varying

levels of automation security in accordance with security analysis tools,

security validation tools and/or security learning systems. The security

analysis tool receives abstract factory models or descriptions for input and

generates an output that can include security guidelines, components,

topologies, procedures, rules, policies, and the like for deployment in an

automation security network. The validation tools are operative in the

automation security network, wherein the tools perform security checking

and/or auditing functions, for example, to determine if security components

are in place and/or in suitable working order. The security learning system

monitors/learns network traffic patterns during a learning phase, fires

alarms or events based upon detected deviations from the learned patterns,

and/or causes other automated actions to occur.'

[0015].

[0016]. US7278156B2 - System and method for enforcing security service

level agreements presents "Systems and methods for providing e-business

services based on security SLAs (service level agreements) in a hosted

computing environment. More specifically, the systems and methods enable

efficient enforcement of individualized security SLAs, wherein

individualized SLA agreements are specified, mapped into security rules

and continually monitored against system events via an efficient rule index

to determine security violations and trigger proper actions.'

[0017]. US4462022A - Security system with radio frequency coupled

remote sensors presents "wireless security system in which a sensor for

detecting a security violation is provided with a radio frequency transmitter

adapted to excite the receiver of a control unit at a different location, the

transmitter of the sensor radiating a signal responsive to the occurrence of a

security violation. The sensor also having means to periodically excite the

transmitter after the lapse of a period of time to indicate that the sensor is in

proper working order, that period varying randomly. The control unit is

provided with a memory and stores responses to the random signals, and at

intervals long with respect to the random periods, samples the memory. The

control unit responds to the absence of a stored response from the

transmissions of the sensor. In a preferred construction, a plurality of

sensors is employed with a single control unit, each of the sensors radiating

a unique encoded signal. The control unit may thus determine by sampling

which of the sensors has failed to radiate a signal received by the control

unit during the sampling interval of the control unit.".

[0018]. Groupings of alternative elements or embodiments of the invention

disclosed herein are not to be construed as limitations. Each group member

can be referred to and claimed individually or in any combination with other

members of the group or other elements found herein. One or more members

of a group can be included in, or deleted from, a group for reasons of

convenience and/or patentability. When any such inclusion or deletion

occurs, the specification is herein deemed to contain the group as modified,

thus fulfilling the written description of all Markus groups used in the

appended claims.

[0019]. As used in the description herein and throughout the claims that

follow, the meaning of "a," "an," and "the" includes plural reference unless

the context clearly dictates otherwise. Also, as used in the description

herein, the meaning of"in" includes "in" and "on"unless the context clearly

dictates otherwise.

[0020]. The recitation of ranges of values herein is merely intended to serve

as a shorthand method of referring individually to each separate value

falling within the range. Unless otherwise indicated herein, each individual

value is incorporated into the specification as if it were individually recited

herein. All methods described herein can be performed in any suitable order

unless otherwise indicated herein or otherwise clearly contradicted by

context.

[0021]. The use of any and all examples, or exemplary language (e.g. "Such

as") provided with respect to certain embodiments herein is intended merely

to better illuminate the invention and does not pose a limitation on the scope

of the invention otherwise claimed. No language in the specification should

be construed as indicating any non-claimed element essential to the practice

of the invention.

[0022]. The above information disclosed in this Background section is only

for the enhancement of understanding of the background of the invention

and therefore it may contain information that does not form the prior art that

is already known in this country to a person of ordinary skill in the art.

SUMMARY

[0023]. Before the present systems and methods, are described, it is to be

understood that this application is not limited to the particular systems, and

methodologies described, as there can be multiple possible embodiments

which are not expressly illustrated in the present disclosure. It is also to be

understood that the terminology used in the description is for the purpose of

describing the particular versions or embodiments only and is not intended

to limit the scope of the present application.

[0024]. The present invention mainly cures and solves the technical

problems existing in the prior art. In response to these problems, the present

invention discloses a System for issue alert of security breach using machine

learning and fuzzy logic.

[0025]. Embodiments of the present invention provide a method, system,

and program product to generate safety alerts is provided. A processor

retrieves a plurality of measurements associated with a location. A processor

determines a set of features based on the plurality of measurements. A

processor identifies a set of membership functions for the set of features. A

processor determines a safety index for the body of water based on the set

of membership functions and one or more input value ranges for the set of

features. In response to the safety index being above a threshold value, a

processor sends an alert to one or more users regarding the location.

[0026]. Present invention discloses. A system issue alert of security breach

using machine learning and fuzzy logic to generate safety alerts, wherein

the system characterized in that:

[0027]. A processor retrieves a plurality of measurements associated with a

location, wherein the processor determines a set of features based on the

plurality of measurements, the processor identifies a set of membership

functions for the set of feature & determines a safety index for the body of

water based on the set of membership functions and one or more input value

ranges for the set of features, and In response to the safety index being above

a threshold value, a processor sends an alert to one or more users regarding

the location.

OBJECTIVE OF THE INVENTION

[0028]. The principle objective of the present invention is to provide a

System for issue alert of security breach using machine learning and fuzzy

logic.

BRIEF DESCRIPTION OF DRAWINGS

[0029]. To clarify various aspects of some example embodiments of the

present invention, a more particular description of the invention will be

rendered by reference to specific embodiments thereof which are illustrated

in the appended drawings. It is appreciated that these drawings depict only

illustrated embodiments of the invention and are therefore not to be

considered limiting of its scope. The invention will be described and explained with additional specificity and detail through the use of the accompanying drawings.

[0030]. In order that the advantages of the present invention will be easily

understood, a detailed description of the invention is discussed below in

conjunction with the appended drawings, which, however, should not be

considered to limit the scope of the invention to the accompanying

drawings, in which:

[0031]. Figure 1 shows a block -diagram for a System for issue alert of

security breach using machine learning and fuzzy logic., according to one

of the embodiment of the present invention.

DETAIL DESCRIPTION

[0032]. The present invention is related to System for issue alert of security

breach using machine learning and fuzzy logic

[0033]. Figure 1 shows a block -diagram for a System for issue alert of

security breach using machine learning and fuzzy logic., according to one

of the embodiment of the present invention.

[0034]. Although the present disclosure has been described with the purpose

of System for issue alert of security breach using machine learning and

fuzzy logic, it should be appreciated that the same has been done merely to

illustrate the invention in an exemplary manner and to highlight any other

purpose or function for which explained structures or configurations could

be used and is covered within the scope of the present disclosure.

[0035]. Some embodiments of this disclosure, illustrating all its features,

will now be discussed in detail. The words and other forms thereof, are

intended to be open ended in that an item or items following any one of

these words are not meant to be an exhaustive listing of such item or items,

or meant to be limited to only the listed item or items. It must also be noted

that as used herein and in the appended claims, the singular forms "a," "an,"

and "the" include plural references unless the context clearly dictates

otherwise. Although any systems and methods similar or equivalent to those

described herein can be used in the practice or testing of embodiments of

the present disclosure, the exemplary systems and methods are now

described. The disclosed embodiments are merely exemplary of the

disclosure, which may be embodied in various forms.

[0036]. The invention relates to a method for the real-time predictive

monitoring of faults of indicators resulting from a smart manufacturing system for supporting the industry. The prediction is based on machine learning algorithms, and the data obtained in real time from the machinery is converted into actions represented by alerts, instant messages and indicators in panels for decision-making or dashboards placed strategically in the production line.

[0037]. Embodiments of the present invention provide a method, system,

and program product to generate safety alerts is provided. A processor

retrieves a plurality of measurements associated with a location. A processor

determines a set of features based on the plurality of measurements. A

processor identifies a set of membership functions for the set of features. A

processor determines a safety index for the body of water based on the set

of membership functions and one or more input value ranges for the set of

features. In response to the safety index being above a threshold value, a

processor sends an alert to one or more users regarding the location.

[0038]. While solutions alert systems are known, they typically only

consider a few measurements when generating an alert. For example, water

safety for a location can be important to both public (e.g., breach attendees)

or private (e.g., a port) entities. Prior water safety alert systems would only

look at a metric such as microbial or algae content. Furthermore, prior water

safety alert systems would typically be specifically designed for a given areas acceptable levels for use by the public or private sectors, with the measurements monitored and the acceptable amounts being unchanged.

Embodiments of the present invention recognize that by including multiple

features, selecting and removing the features from a set, and using the

selected feature set in a fuzzy logic model, that improvements in accuracy

and robustness of a water safety alert systems are provided. By utilizing

unsupervised and supervised machine learning techniques, embodiments of

the present invention provide improvements to the accuracy of water safety

alert systems.

[0039]. The present invention may be a system, a method, and/or a

computer program product. The computer program product may include a

computer readable storage medium (or media) having computer readable

program instructions thereon for causing a processor to carry out aspects of

the present invention.

[0040]. The computer readable storage medium can be a tangible device

that can retain and store instructions for use by an instruction execution

device. The computer readable storage medium may be, for example, but is

not limited to, an electronic storage device, a magnetic storage device, an

optical storage device, an electromagnetic storage device, a semiconductor

storage device, or any suitable combination of the foregoing. A non exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.

[0041]. A processor retrieves a plurality of measurements associated with a

location. A processor determines a set of features based on the plurality of

measurements. A processor identifies a set of membership functions for the

set of features. A processor determines a safety index for the body of water

based on the set of membership functions and one or more input value

ranges for the set of features. In response to the safety index being above a threshold value, a processor sends an alert to one or more users regarding the location.

[0042]. Computer readable program instructions described herein can be

downloaded to respective computing/processing devices from a computer

readable storage medium or to an external computer or external storage

device via a network, for example, the Internet, a local area network, a wide

area network and/or a wireless network. The network may comprise copper

transmission cables, optical transmission fibers, wireless transmission,

routers, firewalls, switches, gateway computers and/or edge servers. A

network adapter card or network interface in each computing/processing

device receives computer readable program instructions from the network

and forwards the computer readable program instructions for storage in a

computer readable storage medium within the respective

computing/processingdevice.

[0043]. Computer readable program instructions for carrying out

operations of the present invention may be assembler instructions,

instruction-set-architecture (ISA) instructions, machine instructions,

machine dependent instructions, microcode, firmware instructions, state

setting data, or either source code or object code written in any combination

of one or more programming languages, including an object oriented programming language such as Smalltalk, C++ or the like, and conventional procedural programming languages, such as the "C"programming language or similar programming languages. The computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network

(LAN) or a wide area network (WAN), or the connection may be made to

an external computer (for example, through the Internet using an Internet

Service Provider). In some embodiments, electronic circuitry including, for

example, programmable logic circuitry, field-programmable gate arrays

(FPGA), or programmable logic arrays (PLA) may execute the computer

readable program instructions by utilizing state information of the computer

readable program instructions to personalize the electronic circuitry, in

order to perform aspects of the present invention.

[0044]. These computer readable program instructions may be provided

to a processor of a general purpose computer, special purpose computer, or

other programmable data processing apparatus to produce a machine, such

that the instructions, which execute via the processor of the computer or other programmable data processing apparatus. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act.

[0045]. The computer readable program instructions may also be loaded

onto a computer, other programmable data processing apparatus, or other

device to cause a series of operational steps to be performed on the

computer, other programmable apparatus or other device to produce a

computer implemented process, such that the instructions which execute on

the computer, other programmable apparatus, or other device implement the

functions/acts.

[0046]. Although implementations of the invention have been described in

a language specific to structural features and/or methods, it is to be

understood that the appended claims are not necessarily limited to the

specific features or methods described. Rather, the specific features and

methods are disclosed as examples of implementations of the invention.

Claims (1)

CLAIMS We claim:

1. A system issue alert of security breach using

machine learning and fuzzy logic to generate safety

alerts, wherein the system characterized in that:

A processor retrieves a plurality of measurements

associated with a location, wherein the processor

determines a set of features based on the plurality of

measurements, the processor identifies a set of

membership functions for the set of feature & determines a safety index for the body of water based on the set of membership functions and one or more input value ranges for the set of features, and In response to the safety index being above a threshold value, a processor sends an alert to one or more users regarding the location.